Waymo is an autonomous driving technology company with the mission to be the most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo One, a fully autonomous ride-hailing service, and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over one million rider-only trips, enabled by its experience autonomously driving tens of millions of miles on public roads and tens of billions in simulation across 13+ U.S. states.

In this role, you'll:

• Report into the TLM of ML performance
• Profile and debug model performance bottlenecks.
• Improve model and data ingestion operations to reduce compute costs.
• Implement novel custom kernels to improve performance and cost.
• Suggest alternative modeling architectures that balance performance and quality.
• Design and implement benchmarks to track performance optimization.
• Work across Planner, Research, Evaluation to improve both simulation and on-board performance.

At a minimum we'd like you to have:

• Advanced degree in Computer Science, Machine Learning, Robotics, similar technical field of study, or equivalent practical experience
• Experience with popular ML frameworks such as JAX, PyTorch, or TensorFlow
• Code and testing skills in Python
• Experience with GPU programming / optimization using CUDA or similar technologies.
• Prior experience optimizing ML model performance e.g. quantization, architectural optimizations (e.g. kv-caching, flash attention, distillation) or low-level optimization (e.g. CUDA kernels, XLA)

It's preferred if you have:

• PhD degree in Computer Science or a similar discipline, or an equivalent amount of deep learning experience
• 4+ years of computer science or deep learning experience
• Experience implementing benchmark models and improving their performance
• Experience with model optimization work deployed in industrial settings
• Low-level Tensorflow experience related to performance (e.g. memory management, real-time / batch processing use-cases)
• Code and testing skills in C++

#LI-Hybrid

The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. 

Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.